Variation of sea ice and perspectives of the Northwest Passage in the Arctic Ocean
Bibliographic record
Abstract
The continued warming of the Arctic atmosphere and ocean has led to a record retreat of sea ice in the last decades. This retreat has increased the probability of the opening of the Arctic Passages in the near future. The Northwest Passage (NWP) is the most direct shipping route between the Atlantic and Pacific Oceans, producing notable economic benefits. Decadal variations of sea ice and its influencing factors from a high-resolution unstructured-grid finite-volume community ocean model were investigated along the NWP in 1988–2016, and the accessibility of the NWP was assessed under shared socioeconomic pathways (SSP245 and 585) and two vessel classes with the Arctic transportation accessibility model in 2021–2050. Sea ice thickness has decreased with increasing seawater temperature and salinity, especially within the Canadian Arctic Archipelago (CAA) in 1988–2016, which has facilitated the opening of the NWP. Complete ship navigation is projected to be possible for polar class 6 ships in August–December in 2021–2025, after when it may extends to July under SSP585 in 2026–2030, while open water ships will not be able to pass through the NWP until September in mid-21st century. The navigability of the NWP is mainly affected by the ice within the CAA. For the accessibility of the Parry Channel, the west part is worse than that of the eastern part, especially in the Viscount-Melville Sound.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".